Analyzing Nitrogen in Silicate Glasses by Secondary Ion Mass Spectrometry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
abstract: Volcanic devolatilization is one of the major processes in the global nitrogen cycle. Past studies have often estimated the magnitude of this flux using volcanic emission measurements, which are limited to currently active systems and sensitive to atmospheric contamination. A different methodological approach requires appropriate analytical parameters for nitrogen analysis in silicate glasses by secondary ion mass spectrometry (SIMS), which have not yet been established. To this end, we analyze various ion implanted basaltic and rhyolitic glasses by SIMS. We demonstrate that water content significantly affects the ion yields of 14N+ and 14N16Oâ, as well as the background intensity of 14N+ and 12C+. Application of implant-derived calibrations to natural samples provide the first reported concentrations of nitrogen in melt inclusions. These measurements are from samples from the Bishop Tuff in California, the Huckleberry Ridge Tuff of the Yellowstone Volcanic Center, and material from the Okaia and Oruanui eruptions in the Taupo Volcanic Center. In all studied material, we find maximum nitrogen contents of less than 45 ppm and that nitrogen concentration varies positively with CO2 concentration, which is interpreted to reflect partial degassing trend. Using the maximum measured nitrogen contents for each eruption, we find that the Bishop released >3.6 x 1013 g of nitrogen, the Huckleberry Ridge released >1.3 x 1014 g, the Okaia released >1.1 x 1011 g of nitrogen, the Oruanui released >4.7 x 1013 g of nitrogen. Simple calculations suggest that with concentrations such as these, rhyolitic eruptions may ephemerally increase the nitrogen flux to the atmosphere, but are insignificant compared to the 4 x 1021 g of nitrogen stored in the atmosphere.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it